Penerapan Data Mining Untuk Memprediksi Prestasi Siswa SMA Pada Dinas Pendidikan Provinsi Jambi
Abstrak
The implementation of education is one of the important efforts in improving the quality of students. With good education it will be useful in realizing the goals of students. This study utilizes data mining techniques using yahoo K-Nearest Neighbor (K-NN) to predict student achievement. The attributes used in this study are scores: Indonesian, Mathematics, English, Biology, Chemistry, Physics, Sociology, Economics, Geography and the target is the study of students. From the results of the study, the best results were at K = 3, the use of python sklean data mining got an accuracy value 61.9% and error MSE 0.8 by comparison Naive Baiyes with accuracy 58% and error MSE 0.41 , and for Rapid miners using KNN got value accucary51%.
Unduhan
Referensi
Abdullah, T. Mohd, dkk. 2015. A Survey of Anomaly Detection Using Data Mining Methods for Hypertext Transfer Protocol Web Services, Journal of Computer Science. Volume 11. No,1, 2015.
Larose, D.T & Larose, C.T. 2014. Discovering Knowledge In Data An Introductionto Data Mining. New Jersey: Willey.
Budiman, dkk .2015. Penerapan Fungsi Data Mining Klasifikasi untuk Prediksi Masa Studi Mahasiswa Tepat Waktu pada Sistem Informasi Akademik Perguruan Tinggi. Jurnal Penelitian Ilmu dan Teknologi Komputer, Vol 7 No 1 (2015): Jupiter April 2015.
F. Yang and F. W. B. Li. Study on student performance estimation, student progress analysis, and student potential prediction based on data mining, Comput. Educ., vol. 123, pp. 97–108, Aug. 2018.
Gunawan, Harry, and Vega Purwayoga. "Data Mining Menggunakan Algoritma K-Means Clustering Untuk Mengetahui Potensi Penyebaran Virus Corona di Kota Cirebon." Jurnal Sisfokom (Sistem Informasi dan Komputer) 11.1 (2022): 1-8.
Mardi, Yuli (2014) Analisa Data Rekam Medis untuk Menentukan Penyakit Terbanyak Berdasarkan International Classification Of Disease (ICD) Menggunakan Decision Tree C4.5 (Studi Kasus : RSU. CBMC Padang). UPI YPTK Padang
Bramer, Max (2007), Principles of Data Mining, Springer Science.
Laudon & Laudon. 2020. Management Information Systems (Sixteenth). United Kingdom: Pearson Education.
Kantardzic, Mehmed (2020), Data Mining: Concepts, Models, Methods, And Algorithms, Edisi ke-3, New Jersey: John Wiley & Sons, Inc.
Pine, J. David. 2019. Introduction to Python for Science and Engineering (Series in Computational Physics). New York: CRC Press.